learning – teaching – research – design – technology

Judy Robertson has a nice story about a student from her interactive design class, who started the course with grave reservations about the use of Second Life, and added with an achievement award and a rewarding experience. She comments on the recent Guardian article and about other students’ feedback from the course. Judy notes:

I suspect there is a feeling among students that Second Life is sad. They may feel self concious about using it, or worry that they are wasting their time. In fact, after just quickly casting my eye over the module feedback forms there are some comments that the students don’t see how it helps them for employment.

SL may be sad as an social activity environment, but that’s beside the point. The question that should concern teachers and students is how good it is in terms of supporting learning.
The things I find sad are the motivation argument and the vocational one.
Saying “oh, here’s a cool environment / technology / game, maybe if we use it for teaching students won’t be so miserable” assumes that learning cannot be its own reward. I know you never said anything like that, but that is a prevalent rhetoric.
Saying “I can’t see how it will help me get a job” is the flip side of the same coin. It’s students assuming that learning is a form of misery which is aimed at preparing them for a greater form of misery (work).
Perhaps we need to make a stance here: we, as teachers, have a duty of pleasure. We should be committed to enabling our students to enjoy learning and enjoy the work that they will do in the future. We also have a duty to enjoy what we do, because otherwise we have no chance with the other two.

Last week I gave a talk on, basically, the corrections I need to do for my thesis.

Anna Sfard commented that (if I understood her correctly) “if that’s your model of narrative, then you should be able to find linguistic markers for it in student texts”

I thought yeah. And then the ol’ computer scientist in me thinks, in that case I should be able to write a parser to do it for me. i.e., instead of parsing text for Chomskian grammar, parse it for narrative structure. Then use that to determine stuff like voice, semantic sequencing, genre. Spotting shifts in these paramaters (e.g from imaginative to paradigmatic) could help identify critical learning points.